Question: EXERCISE 4.36. In Example 4.20, use Eq. 4.16 to verify that the fake spheres with a = 2 and a = , have no umbilical

EXERCISE 4.36. In Example 4.20, use Eq. 4.16 toEXERCISE 4.36. In Example 4.20, use Eq. 4.16 toEXERCISE 4.36. In Example 4.20, use Eq. 4.16 toEXERCISE 4.36. In Example 4.20, use Eq. 4.16 to
EXERCISE 4.36. In Example 4.20, use Eq. 4.16 to verify that the fake spheres with a = 2 and a = , have no umbilical points. (4.16) T. EXAMPLE 4.20 (Fake Spheres). We wish to construct surfaces of revolution with constant Gaussian curvature equal to 1. If K = 1, then Eq. 4.15 says that x" = -x. The following is a solution for every a > 0: (4.17) x(t) = a cos(t). The hypothesis that y is parametrizationgth, so (x')2 + (2')2 = 1, means that z is determined by x as follows: (4.18) = (t) = VI - x'(s)2 ds = 1 - a2 sin? (s) ds. (4.15) K1. Consider the simple regression model: V/i = Po+ Piri +ui, for i = 1, ..., n, with E(ur,) 7 0 and let z be a dummy instrumental variable for a, such that we can write: with E(uilz;) = 0 and E(vilzi) = 0. (c) Denote by no, the number of observations for which z =0 and by n, the number of observations for which z, = 1. Show that: (a - 2) = =(n-m). 1=1 and that: [(8 -=)(3: - 9) = 7 "(n - ni) (31 - 90) . where to and g are the sample means of y for z equal to 0 and 1 respectively. (Hint: Use the fact that n = nj + no, and that = = m). (d) Now we regress y on i to obtain an estimator of 81. From the standard formula of the slope estimator for an OLS regression and using the result in (c), show that: By1 - 90 I1 - To This estimator is called the Wald estimator.1. Consider the simple regression model: yi = Po+ Biz, + ui, for i = 1, ... . n. with E(uilx;) # 0 and let z be a dummy instrumental variable for z, such that we can write: Ti = no + 12+ vi, with E(uilz;) = 0 and E(vilz;) = 0. a) show that no = To, and #1 = 21 - 10, where ro and I, are the sample means of a for 2 equal to 0 and 1 respectively. (b) Define: i; = Fo + (21 - 10) Zi, show that, I, - I = (1, - To) (2, - 2), where ? is the sample mean of z. solve both parts, econometrics8= Bot ByX Assumption (Under simple linear regression model ) I . X2 .... Xn are nonrandom II. X1 .. X, are not all equa III . E ( Us ) =0, E ( U. ) = 0.. E ( un) = 0 IZ. var (us) = var (U2)= var(us) In other words, var (ulx) cdoes not depend on X ( HomesKaclasticty ) V. Us, Uz.. Un are mutually indeperant Provide a mathematical proof for the equation E (62 ) = 62 using assumptions I! - V. 62 = n - 2 n

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